Posts related to my YouTube videos
Variational Graph Autoencoder implemented using Jax & Jraph
Oxford MSc thesis. variational autoencoder combined with graph convolutional networks for learning locally-aware spatial prior distributions
Simplified, reproducible reimplementation of DeepMind's GraphCast weather model using graph neural networks (JAX · Haiku · Jraph). Runs on a single GPU, with honest negative-results reporting and detailed failure-mode analysis of a heavily scaled-down forecasting model.
Molecular active learning with JAX
Reinforcement Learning (RL) environments for a range of graph problems. Written in Jraph.
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